NWNR100350 Data science (UIW)

Type
course with continuous assessment
Semester hours
2
Lecturer (assistant)
Organisation
Statistics
Offered in
Sommersemester 2026
Languages of instruction
Deutsch
Content

- Fundamentals of programming (with R Studio), computational thinking
- Data acquisition using examples of various data sources and data types in coordination with applied modules of the UIW program
- Data preparation
- Data visualization and interpretation
- Creation of simple scientific reports
- Data journalism (explaining data in an easily understandable way and presenting it as a seminar paper in the form of a mini-article with selected graphics)
Previous knowledge expected

Basic knowledge of mathematics.
Objective (expected results of study and acquired competences)

Knowledge:
Students can describe important data sources, explain their basic data structures, and outline how to efficiently access, prepare, structure, and analyze them for data analysis. They can describe basic programming structures and know how to apply them for data preparation, analysis, and visualization. They are capable of professionally describing the process of analysis and documentation.
Skills:
Students can create simple programs and algorithms in the R programming language. This enables them to import, prepare, analyze, visualize, and document larger data structures.
Professional/Occupational Competencies:
Students are capable of independently collecting the required data in a statistically meaningful way, preparing it, and scientifically documenting the analyses in terms of the algorithms, methods, and results used.
Personal Competencies:
Students can communicate in a way that is understandable to non-experts.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.